toki-en-mt
This model is a fine-tuned version of Helsinki-NLP/opus-mt-ROMANCE-en on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2840
- Bleu: 26.7612
- Gen Len: 9.0631
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
---|---|---|---|---|---|
1.7228 | 1.0 | 1260 | 1.4572 | 19.9464 | 9.2177 |
1.3182 | 2.0 | 2520 | 1.3356 | 22.4628 | 9.1263 |
1.1241 | 3.0 | 3780 | 1.3028 | 23.5152 | 9.0462 |
0.9995 | 4.0 | 5040 | 1.2784 | 23.9526 | 9.1697 |
0.8945 | 5.0 | 6300 | 1.2739 | 24.7707 | 9.0914 |
0.8331 | 6.0 | 7560 | 1.2725 | 25.3477 | 9.0518 |
0.7641 | 7.0 | 8820 | 1.2770 | 26.165 | 9.0245 |
0.7163 | 8.0 | 10080 | 1.2809 | 25.8053 | 9.0933 |
0.6886 | 9.0 | 11340 | 1.2799 | 26.5752 | 9.0669 |
0.6627 | 10.0 | 12600 | 1.2840 | 26.7612 | 9.0631 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.3.2
- Tokenizers 0.12.1
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